The article explains the concept of Markov Chain Process, which involves different components like initial state vector, transition probabilities, and steady-state vector. It categorizes this process into two types based on whether the time between states is discrete or continuous. The researchers provide examples and solve them to illustrate how Markov Chain Processes work.