Spelling errors are one of the crucial problems to be addressed in Natural Language Processing tasks. In this study,a context-based automatic spell correction method for Turkish texts is presented. The method combines the Noisy Channel Model with Hidden Markov Models to correct a given word. This study deviates from the other studies by also considering the contextual information of the word within the sentence. The proposed method is aimed to be integrated to other word-based spelling correction models.