Bayesian methods are a set of statistical techniques and principles used for inferring probabilities and making predictions based on prior knowledge and new data. These methods are based on Bayes' theorem, which describes how the probability of a hypothesis can be updated in light of new evidence. Bayesian methods are widely used in various fields such as machine learning, economics, and neuroscience for tasks such as parameter estimation, hypothesis testing, and model comparison. They provide a flexible framework for incorporating subjective beliefs, uncertainty, and prior information into statistical analysis.