This lecture covers the theory of Markov chains, focusing on reversible chains, detailed balance, and the Metropolis-Hastings algorithm. It explains convergence to various distributions and the concept of an invariant distribution. The instructor discusses the properties of Markov chains and their applications in stochastic simulation.