**Core Concept**
The concept being tested here is the definition of a key term in epidemiology, specifically the ability of a test to accurately identify individuals without the disease (true negatives).

**Why the Correct Answer is Right**
Specificity measures the proportion of true negatives correctly identified by a test. In other words, it estimates the probability that a person without the disease will test negative. This is crucial in public health and clinical practice, as it helps to avoid unnecessary treatments and false alarms. A high specificity indicates that the test is good at distinguishing between people with and without the disease.

**Why Each Wrong Option is Incorrect**
**Option A:** Sensitivity measures the proportion of true positives correctly identified by a test, not true negatives. It estimates the probability that a person with the disease will test positive.
**Option C:** Positive Predictive Value (PPV) is the proportion of true positives among all positive results. It does not relate to the detection of true negatives.
**Option D:** Negative Predictive Value (NPV) is the proportion of true negatives among all negative results. While it is related to the detection of true negatives, it is not the same as specificity.

**Clinical Pearl / High-Yield Fact**
Remember, specificity is often more important than sensitivity in certain clinical scenarios, such as screening tests for diseases with low prevalence.

**✓ Correct Answer: B. Specificity**