The Bayes classifier is a powerful tool in pattern recognition that minimizes errors in classifying patterns. It works by using prior probabilities and pattern distributions to calculate posterior probabilities and assign class labels. By choosing the class with the highest posterior probability, the classifier accurately labels test patterns. This method is based on Bayes theorem and likelihood values to make informed decisions about pattern classification.