Bayesian Methods are a statistical approach that applies Bayes' Theorem to update the probability of a hypothesis as more evidence or information becomes available. This method allows for the incorporation of prior knowledge or beliefs, which can be adjusted as new data is collected, making it particularly useful in fields like machine learning, medicine, and economics. In Bayesian analysis, probabilities are treated as degrees of belief rather than fixed frequencies. This flexibility enables practitioners to model uncertainty more effectively and make informed decisions based on both prior information and current observations, leading to more robust conclusions in various applications.