Brilliant provides a great definition of Markov chains (here):
“A Markov chain is a mathematical system that experiences transitions from one state to another according to certain probabilistic rules. The defining characteristic of a Markov chain is that no matter how the process arrived at its present state, the possible future states are fixed. In other words, the probability of transitioning to any particular state is dependent solely on the current state and time elapsed.”
The actual math behind Markov chains requires knowledge on linear algebra and matrices, so I’ll leave some links below in case you want to explore this topic further on your own.
