Write the partitioned mean as and assume is nonsingular, as required by the displayed inverse. For the conditional multivariate normal distribution, form the residual
A linear transformation of a multivariate normal distribution is again normal. Direct calculation gives
The jointly normal blocks and are therefore independent: their joint characteristic function has no cross term in its quadratic exponent and factors into the two marginal characteristic functions. Conditioning leaves the distribution of unchanged. Reconstructing proves the full conditional law, including the requested Schur complement covariance:
This describes a regular conditional law; it does not require the equality event to have positive probability.

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