The Iris Classification project involves classifying iris flowers into three species (setosa, versicolor, virginica) based on sepal and petal measurements. Key steps include data exploration, preprocessing, model selection (e.g., Logistic Regression, KNN, Decision Trees), training, evaluation, and tuning. The goal is to accurately classify iris species, demonstrating core machine learning concepts.