The Exponential Forgetting Factor is a mathematical concept used to model the decay of memory or information over time, emphasizing that more recent information is weighted more heavily than older information. It's crucial in algorithms and systems where the relevance of data diminishes exponentially with time, such as in adaptive filters, machine learning models, and time-series analysis.