Congestion Control (CC) limits the transmission rate of data packets in the transport layer protocol, e.g., in TCP and QUIC, of a sending endpoint so as to mitigate the congestion in packet-switched communication networks. Numerous studies have developed and evaluated Congestion Control Algorithms (CCAs) for a wide range of network types. Prior surveys have covered the functioning of the existing CCAs and their performance characteristics. In contrast, this survey focuses on the quantitative evaluation of CCAs; specifically, we comprehensively survey the CCA evaluation methodologies, i.e., the why and how of CCA evaluations. We define a CCA evaluation as a combination of a prescribed evaluation scenario with prescribed evaluation metrics. In turn, we define an evaluation scenario as a combination of a prescribed network (e.g., path) model and a particular traffic model. We present comprehensive sets of network and traffic model characteristics (i.e., network scenario characteristics) that can influence the performance of CCAs, as well as a comprehensive set of evaluation metrics for measuring the performance of CCAs. We taxonomize CCA evaluations into the main categories: Steady-state, transient-state, network variation, dynamic (e.g., wireless) network, and competition evaluations. We place and survey the existing CCA evaluation studies in this taxonomy to uncover the main trends and shortcomings of the CCA evaluation field to date. To facilitate the comprehensive rigorous evaluation of CCAs, we have developed the publicly available CCA evaluation framework ccperf, which incorporates the insights from our survey. We also outline future research directions to further advance the comprehensive rigorous evaluation of CCAs.