This study aims to develop an Adaptive Neuro-Fuzzy Inference System (ANFIS) that integrates Hedge Algebra to handle uncertainties and linguistic variables more effectively. Hedge Algebra is used to enhance the interpretability and adaptability of the system. The proposed model incorporates Hedge Algebra to manage the semantic meanings of linguistic terms within the fuzzy inference system. The adaptability of the system is achieved through reinforcement learning mechanisms, enabling it to refine its fuzzy rules and membership functions dynamically. This research bridges the gap between traditional fuzzy systems and Hedge Algebra, offering a robust framework for applications requiring nuanced linguistic reasoning and adaptability.