In the context of Markov chains, a recurrent state is one that the process will return to with probability one, meaning it is guaranteed to be visited infinitely often. Recurrent states are pivotal in understanding the long-term behavior of stochastic processes, as they provide insights into the stability and ergodicity of the system.