In this paper, a maximum a posteriori sound source localization (MAP-SSL) is proposed in reverberant and noisy conditions. Incorporating a sparse prior related to the location of source into the existing maximum likelihood sound source localization (ML-SSL) framework, the proposed MAP-SSL algorithm is derived. In the proposed MAP-SSL algorithm, assuming the direction of an active source to be sparse in the space of all possible finite source directions, when a source is active, the criterion in deriving the proposed MAP-SSL algorithm is similar to the criterion used to derive the existing ML-SSL framework, except that in our criterion a sparse source prior that enforces a sparse source direction solution is added. The sparse source prior plays a key role in improving the SSL performance. The experimental results show the proposed MAP-SSL algorithm outperforms the variants of the ML-SSL framework.