diff --git a/pandas/plotting/_matplotlib/converter.py b/pandas/plotting/_matplotlib/converter.py
index 0eb3318ac96c5..e2121526c16af 100644
--- a/pandas/plotting/_matplotlib/converter.py
+++ b/pandas/plotting/_matplotlib/converter.py
@@ -4,7 +4,6 @@
 import datetime as pydt
 from datetime import (
     datetime,
-    timedelta,
     tzinfo,
 )
 import functools
@@ -460,28 +459,6 @@ def autoscale(self):
         return self.nonsingular(vmin, vmax)
 
 
-def _from_ordinal(x, tz: tzinfo | None = None) -> datetime:
-    ix = int(x)
-    dt = datetime.fromordinal(ix)
-    remainder = float(x) - ix
-    hour, remainder = divmod(24 * remainder, 1)
-    minute, remainder = divmod(60 * remainder, 1)
-    second, remainder = divmod(60 * remainder, 1)
-    microsecond = int(1_000_000 * remainder)
-    if microsecond < 10:
-        microsecond = 0  # compensate for rounding errors
-    dt = datetime(
-        dt.year, dt.month, dt.day, int(hour), int(minute), int(second), microsecond
-    )
-    if tz is not None:
-        dt = dt.astimezone(tz)
-
-    if microsecond > 999990:  # compensate for rounding errors
-        dt += timedelta(microseconds=1_000_000 - microsecond)
-
-    return dt
-
-
 # Fixed frequency dynamic tick locators and formatters
 
 # -------------------------------------------------------------------------
diff --git a/pandas/tests/plotting/test_datetimelike.py b/pandas/tests/plotting/test_datetimelike.py
index 2eb44ef4771e0..7164b7a046ff2 100644
--- a/pandas/tests/plotting/test_datetimelike.py
+++ b/pandas/tests/plotting/test_datetimelike.py
@@ -295,27 +295,6 @@ def test_plot_multiple_inferred_freq(self):
         ser = Series(np.random.default_rng(2).standard_normal(len(dr)), index=dr)
         _check_plot_works(ser.plot)
 
-    @pytest.mark.xfail(reason="Api changed in 3.6.0")
-    def test_uhf(self):
-        import pandas.plotting._matplotlib.converter as conv
-
-        idx = date_range("2012-6-22 21:59:51.960928", freq="ms", periods=500)
-        df = DataFrame(
-            np.random.default_rng(2).standard_normal((len(idx), 2)), index=idx
-        )
-
-        _, ax = mpl.pyplot.subplots()
-        df.plot(ax=ax)
-        axis = ax.get_xaxis()
-
-        tlocs = axis.get_ticklocs()
-        tlabels = axis.get_ticklabels()
-        for loc, label in zip(tlocs, tlabels):
-            xp = conv._from_ordinal(loc).strftime("%H:%M:%S.%f")
-            rs = str(label.get_text())
-            if len(rs):
-                assert xp == rs
-
     def test_irreg_hf(self):
         idx = date_range("2012-6-22 21:59:51", freq="s", periods=10)
         df = DataFrame(