Markov Chain Monte Carlo (MCMC) is a class of algorithms used to sample from probability distributions by constructing a Markov chain that has the desired distribution as its equilibrium distribution. It is particularly useful in Bayesian statistics and computational physics for approximating complex integrals and distributions that are difficult to compute directly.