This lecture covers the concept of Markov chains and stationary distributions, explaining how transitions between states occur with specific probabilities. The instructor discusses the importance of identifying stationary distributions and how they relate to the original chain. By introducing loops with specific probabilities at each state, the lecture demonstrates how to improve convergence in certain scenarios.