List-decoding Fano inequality ($p_e\ge 1-\{I(J;Y)+\log 2\}/\log (N/B)$)

If a uniform index $J$ has $N$ possibilities and every proposed success neighbourhood contains at most $B<N$ possibilities, then any estimator has failure probability at least the displayed expression. Condition on its success indicator: conditional entropy is at most $\log 2+(1-p_e)\log B+p_e\log N$. Subtract this from $\log N$ to bound the mutual information and rearrange. A metric Hamming ball gives approximate recovery rather than exact index decoding.