**Core Concept**
The question is testing the understanding of statistical methods for comparing proportions between two independent groups. In medical research, comparing proportions is crucial for assessing the efficacy of a treatment, the prevalence of a disease, or the association between a risk factor and an outcome.

**Why the Correct Answer is Right**
The appropriate statistical test for comparing two proportions is the **Chi-Square Test**. This test is used when the data are categorical and the sample sizes are sufficiently large. The Chi-Square Test calculates the likelihood that the observed differences between the two groups are due to chance, and it provides a p-value to determine the significance of the difference. The test is widely used in medical research, particularly in studies involving case-control designs or cohort studies.

**Why Each Wrong Option is Incorrect**
**Option A:** This option is incorrect because the **T-test** is used for comparing means between two groups, not proportions. While the T-test can be used for comparing proportions if the sample sizes are sufficiently large, it is not the preferred method.

**Option B:** This option is incorrect because the **Wilcoxon Rank-Sum Test** is a non-parametric test used for comparing distributions between two groups, not proportions. Although it can be used for categorical data, it is not the most appropriate test for comparing proportions.

**Option C:** This option is incorrect because the **Fisher's Exact Test** is used for comparing proportions when the sample sizes are small. While it is a suitable test for small samples, it is not the preferred method for larger samples.

**Clinical Pearl / High-Yield Fact**
A key consideration when selecting a statistical test is to ensure that the test assumptions are met. For the Chi-Square Test, the assumptions include independence of observations, sufficient sample sizes, and no more than 20% of the expected frequencies being less than 5.

**Correct Answer: C. Fisher's Exact Test**