A discrete-time Markov chain is a stochastic process that undergoes transitions from one state to another in a state space, with the probability of each transition depending only on the current state and not on the sequence of events that preceded it. This memoryless property, known as the Markov property, makes it a powerful tool for modeling random systems that evolve over time in discrete steps.