Machine Learning is an academic field with its own particular terminology. Data scientists refer to the values determined from the training features as parameters, so a different term is required for values that are used to configure training behavior but which are not derived from the training data — hence the term hyperparameter.
Hyperparameters are one of the key things in the machine learning as they influence accuracy, readiness of your model to face real life scenario. Hence having a understanding of hyperparameter is a must, and in my opinion one can have considerably good understanding of hyperparameter while performing hyperparameter tuning.