Wave energy flux (WEF) is assessed in the Caribbean Sea from a 60-year (1958--2017) wave hindcast. We use a novel approach, based on neural networks, to identify coherent regions of similar WEF and their association with different climate patterns. This method allows for a better evaluation of the underlying dynamics behind seasonal and inter-annual WEF variability, including the effect induced by the latitudinal migration of the Intertropical Convergence Zone (ITCZ), and the influence of El Ni~no-Southern Oscillation events. Results show clear regional differences of the WEF variability likely due to both a clear regionalization of the WEF due to both the intensification and migration of the ITCZ. WEF exhibits a strong semiseasonal signal in areas of the continental shelf, with maximums in January and June, in agreement with the sea surface temperature and sea level pressure variability. At larger scales, WEF shows a significant correlation with the Oceanic Ni~no Index depicting positive values in the central and western basin and negative ones at the eastern side.