The steady state distribution in a stochastic process is a probability distribution that remains unchanged as time progresses, indicating a system's long-term behavior. It is crucial for understanding the equilibrium properties of Markov chains, where the distribution provides insights into the likelihood of being in different states after a large number of transitions.