Pandas join with multi-index and NaN

I am using Pandas 2.1.3.

I am trying to join two dataframes on multiple index levels, and one of the index levels has NA's. The minimum reproducible example looks something like this:

a = pd.DataFrame({'idx_a':['A', 'A', 'B'],'idx_b':['alpha', 'beta', 'gamma'],'idx_c': [1.0, 1.0, 1.0],'x':[10, 20, 30]}).set_index(['idx_a', 'idx_b', 'idx_c'])b = pd.DataFrame({'idx_b':['gamma', 'delta', 'epsilon', np.nan, np.nan],'idx_c': [1.0, 1.0, 1.0, 1.0, 1.0],'y':[100, 200, 300, 400, 500]}).set_index(['idx_b', 'idx_c'])c = a.join(    b,    how='inner',    on=['idx_b', 'idx_c'])print(a)                    xidx_a idx_b idx_c    A     alpha 1.0    10      beta  1.0    20B     gamma 1.0    30print(b)                yidx_b   idx_c     gamma   1.0    100delta   1.0    200epsilon 1.0    300NaN     1.0    400        1.0    500print(c)                    x    yidx_a idx_b idx_c         B     gamma 1.0    30  100            1.0    30  400            1.0    30  500

I would have expected:

print(c)                    x    yidx_a idx_b idx_c         B     gamma 1.0    30  100

Why is join matching on the NaN values?