This lecture covers the concept of Markov chains, focusing on challenges and surprises that arise when analyzing them. The instructor discusses the convergence of probabilities in a Markov chain, the impact of grouping states on the Markov property, and the implications of different transition probabilities. Through examples and calculations, the lecture explores how Markov chains behave in various scenarios, highlighting both expected and unexpected outcomes.