Naive Bayes Classifier is a simple yet effective probabilistic machine learning model used for classification tasks, based on applying Bayes' theorem with the 'naive' assumption of independence between features. This assumption allows it to work efficiently with large datasets and provides competitive performance for tasks such as text classification despite its simplicity.