Brain tumors are accumulations of atypical cells, malignant or benign. Accurate tumor segmentation from MRI is crucial but time-consuming and error-prone. Deep learning methods, particularly Fuzzy C-Means (FCM) clustering, are common but overlook spatial information, reducing robustness. This study presents Weighted FCM (WFCM) combined with the Artificial Hummingbird Algorithm (AHB) for improved clustering. The method enhances tumor delineation, aiding physicians in rapid diagnosis and informed treatment decisions.