diff --git a/doc/source/whatsnew/v2.1.2.rst b/doc/source/whatsnew/v2.1.2.rst
index a5ba365f2d456..8aba2bcbecf2f 100644
--- a/doc/source/whatsnew/v2.1.2.rst
+++ b/doc/source/whatsnew/v2.1.2.rst
@@ -24,6 +24,7 @@ Bug fixes
 ~~~~~~~~~
 - Fixed bug in :meth:`DataFrame.resample` not respecting ``closed`` and ``label`` arguments for :class:`~pandas.tseries.offsets.BusinessDay` (:issue:`55282`)
 - Fixed bug in :meth:`DataFrame.resample` where bin edges were not correct for :class:`~pandas.tseries.offsets.BusinessDay` (:issue:`55281`)
+- Silence ``Period[B]`` warnings introduced by :issue:`53446` during normal plotting activity (:issue:`55138`)
 -
 
 .. ---------------------------------------------------------------------------
diff --git a/pandas/plotting/_matplotlib/converter.py b/pandas/plotting/_matplotlib/converter.py
index e6408a0eae841..5a7ceabbf554e 100644
--- a/pandas/plotting/_matplotlib/converter.py
+++ b/pandas/plotting/_matplotlib/converter.py
@@ -13,6 +13,7 @@
     Any,
     cast,
 )
+import warnings
 
 import matplotlib.dates as mdates
 from matplotlib.ticker import (
@@ -239,18 +240,29 @@ def _convert_1d(values, units, axis):
         if not hasattr(axis, "freq"):
             raise TypeError("Axis must have `freq` set to convert to Periods")
         valid_types = (str, datetime, Period, pydt.date, pydt.time, np.datetime64)
-        if isinstance(values, valid_types) or is_integer(values) or is_float(values):
-            return get_datevalue(values, axis.freq)
-        elif isinstance(values, PeriodIndex):
-            return values.asfreq(axis.freq).asi8
-        elif isinstance(values, Index):
-            return values.map(lambda x: get_datevalue(x, axis.freq))
-        elif lib.infer_dtype(values, skipna=False) == "period":
-            # https://github.com/pandas-dev/pandas/issues/24304
-            # convert ndarray[period] -> PeriodIndex
-            return PeriodIndex(values, freq=axis.freq).asi8
-        elif isinstance(values, (list, tuple, np.ndarray, Index)):
-            return [get_datevalue(x, axis.freq) for x in values]
+        with warnings.catch_warnings():
+            warnings.filterwarnings(
+                "ignore", "Period with BDay freq is deprecated", category=FutureWarning
+            )
+            warnings.filterwarnings(
+                "ignore", r"PeriodDtype\[B\] is deprecated", category=FutureWarning
+            )
+            if (
+                isinstance(values, valid_types)
+                or is_integer(values)
+                or is_float(values)
+            ):
+                return get_datevalue(values, axis.freq)
+            elif isinstance(values, PeriodIndex):
+                return values.asfreq(axis.freq).asi8
+            elif isinstance(values, Index):
+                return values.map(lambda x: get_datevalue(x, axis.freq))
+            elif lib.infer_dtype(values, skipna=False) == "period":
+                # https://github.com/pandas-dev/pandas/issues/24304
+                # convert ndarray[period] -> PeriodIndex
+                return PeriodIndex(values, freq=axis.freq).asi8
+            elif isinstance(values, (list, tuple, np.ndarray, Index)):
+                return [get_datevalue(x, axis.freq) for x in values]
         return values
 
 
@@ -575,11 +587,18 @@ def _daily_finder(vmin, vmax, freq: BaseOffset) -> np.ndarray:
     (vmin, vmax) = (int(vmin), int(vmax))
     span = vmax - vmin + 1
 
-    dates_ = period_range(
-        start=Period(ordinal=vmin, freq=freq),
-        end=Period(ordinal=vmax, freq=freq),
-        freq=freq,
-    )
+    with warnings.catch_warnings():
+        warnings.filterwarnings(
+            "ignore", "Period with BDay freq is deprecated", category=FutureWarning
+        )
+        warnings.filterwarnings(
+            "ignore", r"PeriodDtype\[B\] is deprecated", category=FutureWarning
+        )
+        dates_ = period_range(
+            start=Period(ordinal=vmin, freq=freq),
+            end=Period(ordinal=vmax, freq=freq),
+            freq=freq,
+        )
 
     # Initialize the output
     info = np.zeros(
@@ -1072,7 +1091,13 @@ def __call__(self, x, pos: int = 0) -> str:
             fmt = self.formatdict.pop(x, "")
             if isinstance(fmt, np.bytes_):
                 fmt = fmt.decode("utf-8")
-            period = Period(ordinal=int(x), freq=self.freq)
+            with warnings.catch_warnings():
+                warnings.filterwarnings(
+                    "ignore",
+                    "Period with BDay freq is deprecated",
+                    category=FutureWarning,
+                )
+                period = Period(ordinal=int(x), freq=self.freq)
             assert isinstance(period, Period)
             return period.strftime(fmt)
 
diff --git a/pandas/tests/plotting/frame/test_frame.py b/pandas/tests/plotting/frame/test_frame.py
index 47114cab47619..2ef1f065f603d 100644
--- a/pandas/tests/plotting/frame/test_frame.py
+++ b/pandas/tests/plotting/frame/test_frame.py
@@ -2487,6 +2487,15 @@ def test_secondary_y(self, secondary_y):
                 assert ax.get_ylim() == (0, 100)
                 assert ax.get_yticks()[0] == 99
 
+    @pytest.mark.slow
+    def test_plot_no_warning(self):
+        # GH 55138
+        # TODO(3.0): this can be removed once Period[B] deprecation is enforced
+        df = tm.makeTimeDataFrame()
+        with tm.assert_produces_warning(False):
+            _ = df.plot()
+            _ = df.T.plot()
+
 
 def _generate_4_axes_via_gridspec():
     import matplotlib.pyplot as plt
diff --git a/pandas/tests/plotting/test_series.py b/pandas/tests/plotting/test_series.py
index e77dc0b305171..6719e39612f5d 100644
--- a/pandas/tests/plotting/test_series.py
+++ b/pandas/tests/plotting/test_series.py
@@ -973,3 +973,10 @@ def test_series_none_color(self):
         ax = series.plot(color=None)
         expected = _unpack_cycler(mpl.pyplot.rcParams)[:1]
         _check_colors(ax.get_lines(), linecolors=expected)
+
+    @pytest.mark.slow
+    def test_plot_no_warning(self, ts):
+        # GH 55138
+        # TODO(3.0): this can be removed once Period[B] deprecation is enforced
+        with tm.assert_produces_warning(False):
+            _ = ts.plot()