Markov Chain Monte Carlo (MCMC) is a method that helps to sample from complex distributions. It uses Markov Chains and the Metropolis-Hastings Algorithm to do this. MCMC is useful for analyzing data and making decisions. It involves concepts like Bayes' theorem, prior and posterior distributions, and Gibbs sampling. The method can handle both simple and complex distributions, making it versatile for various applications.