The MLOps lifecycle refers to the structured set of stages involved in managing machine learning models in production. It encompasses data preparation, model training, evaluation, deployment, monitoring, maintenance, and retiring or replacing models. It aims to ensure the efficient and reliable operation of ML systems throughout their lifecycle.