Skin cancer presents a significant global health concern, with its incidence steadily increasing over recent decades. This disease affects millions worldwide, presenting considerable challenges to healthcare systems and societies. Skin lesions serve as crucial markers for diagnosing and monitoring skin cancer, revealing abnormal cell growth visibly. Given the escalating prevalence of skin cancer and the imperative for early detection, there is a pressing need for computer-aided tools in skin lesion detection. Researchers have utilized artificial intelligence (AI) and deep learning to advance lesion detection, addressing this urgent requirement. Amid the rising prevalence of skin cancer, this paper delves into various deep learning methodologies, including convolutional neural networks (CNNs) and computer vision techniques, which have shown promising outcomes in automating skin lesion detection comparable to expert dermatologists.