[BUG] FallbackForecaster fails with ForecastByLevel when nan_predict_policy='raise'

[ninedigits]

Describe the bug

When forecasting hierarchical time series, such as with ForecastByLevel, the following line may not function as intended and may result in a ValueError being raised.

    def _validate_y_pred(self, y_pred):
        if self.nan_predict_policy in ("warn", "raise"):
            has_nans = y_pred.isnull().any() # Error caused here when using ForecastByLevel

To Reproduce

def test_forecastbylevel_nan_predict():
    from sktime.utils._testing.hierarchical import _make_hierarchical
    from sktime.forecasting.compose import ForecastByLevel

    df = _make_hierarchical(
        hierarchy_levels=(2, 2, 10),
        max_timepoints=10,
        min_timepoints=10,
        same_cutoff=True,
        n_columns=1,
        all_positive=True,
        index_type="period",
        random_state=0,
        add_nan=False,
    )
    forecaster1 = DummyForecaster(raise_at=None, predict_nans=True)
    forecaster2 = NaiveForecaster()
    forecaster = ForecastByLevel(
        FallbackForecaster(
            [
                ("forecaster1_pred_nans", forecaster1),
                ("forecaster2_expected_", forecaster2),
            ],
            nan_predict_policy="raise",
        )
    )
    fh = [1, 2, 3]
    forecaster.fit(y=df, fh=fh)
    y_pred_actual = forecaster.predict()

    forecaster2.fit(y=df, fh=[1, 2, 3])
    y_pred_expected = forecaster2.predict()

    pd.testing.assert_frame_equal(y_pred_expected, y_pred_actual)

Expected behavior

Additional context

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