This research investigates the effectiveness of a K-Means Adaptive Channels strategy for mean reversion trading, aiming to provide an accessible and high-performing alternative to complex deep learning models for retail traders with an advanced knowledge of statistics in finance and programming. Results indicate that the K-Means Adaptive Channels strategy is a statistically profitable system, achieving a 73.68% win rate and an average trade profit of 3.65% in mean-reverting markets. The analysis confirms its outperformance of conventional indicators, such as Bollinger Bands and the Relative Strength Index (RSI), and demonstrates its adaptability to other assets. The research concludes that K-Means Adaptive Channels represent a robust and accessible trading system, with a triple-parameter configuration yielding superior performance. We recommend integrating this strategy with a market regime indicator to optimise its utility and mitigate drawdowns during trending periods.