Markov chains are a simple stochastic model that can explain complex real-world phenomena. They are based on the principle of "memorylessness", where the probability of transitioning to the next state in a process depends only on the current state and not any past states. Some applications of Markov chains include market research, text generation, financial predictions, customer journey analysis, genetics research, music composition, and ranking web pages.