Optuna is not strictly a Bayesian hyperparameter optimizer, but it does incorporate some Bayesian optimization techniques. Optuna mainly uses the Tree-structured Parzen Estimator (TPE) algorithm, which is a sequential model-based optimization method that shares some similarities with Bayesian optimization. Both methods aim to find the optimal hyperparameters by building a probabilistic model of the objective function and using it to guide the search process. However, TPE is more flexible and efficient than traditional Bayesian optimization, making Optuna a powerful choice for hyperparameter tuning in machine learning.